Frequency bands for wireless communications are divided among primary users (PU), which are licensed to use a certain spectrum for a given purpose. For example, cellular networks are allocated a portion of a frequency band for wirelessly transmitting and receiving communication signals, as are frequency modulation (FM) radio stations, television stations, amateur radio, and/or the like. Such partitioning ensures different types of signals can be simultaneously communicated without substantial interference from other sources. The signals can be transmitted in an effort to provide beneficial communication services to one or more users. In many cases, the technologies are allocated large portions of frequency bands. Due to technological limitations (such as signal power), device location, usage patterns, required bandwidth, etc., portions of given frequency bands may be inefficiently utilized and/or wasted. For example, in rural areas, much of frequency bands reserved for FM radio stations can go unutilized as transmitters are more sparsely deployed as compared to urban areas.
In this regard, cognitive radio (CR) technology has evolved, which enables wireless communications over unused portions of the frequency bands. Because use of reserved frequency bands can vary over time, CRs possess a cognitive capability to determine frequencies that are unutilized, as well as an ability to reconfigure parameters to communicate over the unutilized frequencies. The cognitive capability cycle can include spectrum sensing (e.g., radio signal analysis, channel identification, etc.), cognition/management (e.g., dynamic spectrum management, routing, quality-of-service provisioning, etc.), and control action (e.g., transmit-power control, adaptive modulation and coding, rate control, etc.).
Spectrum sensing is used to detect presence of a PU related to a frequency band; if the PU is sufficiently sensed, then the CR might not utilize the related spectrum. Sensing can be performed based on energy detection, which facilitates determining whether the frequency band is utilized; however, energy detection does not allow identification of a user occupying the frequency band. Sensing can also be performed using matched filtering; however, this requires prior knowledge of details related to the system for which the spectrum is reserved as well as synchronization thereto, which can be complex. Sensing can also be performed using feature detection where standards specifics of the related technology can be identified in a signal to determine whether the signal relates to the PU technology. Feature detection, however, is highly complex to implement and operate.